GREP AI is #1 on Every Deep Research Benchmark. Meet Brain.
State-of-the-art on every major deep research benchmark, ahead of OpenAI, Anthropic, Google, Nvidia and Perplexity — and Brain, a new memory architecture.
Today we're sharing that Grep achieved state-of-the-art scores on every major independent deep research benchmark, beating Perplexity, Google, Anthropic, Nvidia and OpenAI.
The Results
No other product holds #1 on more than one of these benchmarks. Grep holds all three.
We're also releasing a new architecture we call Brain, which transforms Grep from a research tool into a system that understands you and your work, compounds your knowledge across research sessions, and turns research into slides, spreadsheets, docs, dashboards and other real work deliverables.
All results, scoring code, and per-question data are published at github.com/Parcha-ai/benchmarks.
Why Deep Research Matters
At Parcha, we spent years building compliance infrastructure, processing hundreds of thousands of requests for fintechs like Airwallex, Flutterwave, and IG.com at 99.7% accuracy. What we learned is that the same principles - deep source verification, structured reasoning, domain expertise - apply far beyond compliance to any knowledge work where being wrong has consequences.
Deep research is the foundation of serious work. The kind of work where being wrong has consequences, where you need to show your sources, and where the quality of your thinking depends on the quality of what you find.
Compliance and AML: A compliance officer screening a counterparty can't rely on a chatbot summary. They need sanctions filings, corporate registries, adverse media from primary sources, and a clear audit trail.
Investor due diligence: Before wiring money, you need to verify cap tables, litigation history, UBO structures, and regulatory standing across multiple jurisdictions.
Underwriting: Lending decisions require business verification, owner background checks, financial analysis, and industry risk assessment, all cross-referenced and documented.
Legal research: Lawyers cite research in court filings. If it's wrong, there are professional consequences. They need case law, regulatory filings, and expert-level analysis they can put their name on.
Market intelligence: Product and strategy teams need competitive analysis, patent landscapes, and market sizing built from real data, not search engine summaries.
Policy and OSINT: Government analysts and investigators need to synthesize across court records, corporate filings, shipping data, and open-source intelligence to build an accurate picture of the world and potential threat vectors.
These are the workflows Grep is built for. Not casual questions. Serious work where the research drives high-stakes decisions.
Since launching as a research preview, Grep has been used for AML compliance, investor due diligence, small business underwriting, market and competitor intelligence, real estate research, and more. It's trusted by professionals at Amazon, Google, Orbital, Astreya, BitcoinSuisse, Craft.co, Shopmonkey and dozens more companies to make high-stakes decisions.
What's New: Grep Brain
With this release, every Grep account gets a dedicated second brain in the cloud. Your own workspace, your own memory, your own team of research experts that help you get serious work done.
It Remembers Everything
Grep Brain learns from every session. The research you did last month, the decisions you made, the context behind them. Come back next week and it picks up where you left off. Your knowledge compounds over time, the way yours does.
It Does the Work, Not Just the Research
Ask Brain to prep you for a board meeting and you get a slide deck, not a wall of text. It builds spreadsheets, reports, dashboards, and documents you can actually send to your team. Real deliverables, not summaries you have to rewrite.
It Goes to the Source
Brain pulls from 90+ trusted data sources: court records, patent registries, sanctions databases, corporate filings, academic papers. Not search engine results. The actual documents. When you cite something from Grep, you can put your name on it.
It Brings the Right Expert to Every Objective
Behind the scenes, 26 specialized AI experts work in parallel, each with deep skills in areas like compliance, financial analysis, legal research, and market intelligence. You ask one question and a team gets to work.
It Gets Smarter With You
Every piece of research, every analysis, every deliverable lives in your workspace and builds on what came before. Brain doesn't start from scratch each time. It compounds - the way a great analyst does after years on the job.
What Users Say
"Our leadership asked if Gemini could do what Grep does. The team tried and it's not even close. Grep is far superior for our underwriting use case."
Crystal Anderson, Leading Risk Strategy & Operations, Shopmonkey
Shopmonkey's underwriting team uses Grep to make faster, more confident credit decisions across thousands of auto repair shops. What used to take hours of manual research now takes minutes. In one case, Stripe flagged a merchant for excessive disputes and was about to shut them down. Crystal ran the business through Grep. The report surfaced a litigation record and a news clipping that initially looked concerning, but the details told a different story: the issues were linked to a closed business, and a former employee had since moved on to work at the flagged shop. Armed with Grep's research, Crystal told Stripe to stand down. The merchant was legitimate.
AI You Can Trust
When a compliance officer signs off on a sanctions report, they're putting their name on it. When a lawyer cites research in a court filing, there are consequences if it's wrong. That's the kind of work our customers do with Grep every day.
Grep performs the way it does on benchmarks because it's loaded with the same expertise those professionals rely on: codified skills paired with trusted, primary data sources. Not a general-purpose model guessing from web results. A system that knows where to look and how to verify what it finds.
The gap between Grep and a standalone frontier model on DRACO is 18.8 percentage points. Same underlying model capabilities. Radically different results. That gap is expertise: 259 skills, 90+ trusted data sources, and an architecture that knows how to use them.
That's the difference between output you trust and output you double-check.
Grep is available now. Try it free or schedule an onboarding call.
Full benchmark data: github.com/Parcha-ai/benchmarks